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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Kaili Mao Jianwei Niu Xuejiao Wang Lei Wang Meikang Qiu State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Department of Computer Science Pace University New York City NY USA

ISBN: (纸本)9781479989386

Product reviews can direct consumers' purchasing behavior and sellers' marketing strategy. Therefor, in this paper, we propose a novel method which combines lexicon-based and learn-based techniques in order to solve cross-domain sentiment analysis of product reviews. We first create three domain lexicons based on the basic lexicon and corpus from three domains containing book, hotel and electronics. Furthermore, we use four kinds of features to build classifiers. Besides, we conduct a series of experiments to evaluate our method by using different lexicons and different classifiers. Experimental results on data of product reviews show that domain lexicons outperform the basic lexicon no matter in which domain. What's more, our method performs much better than the existing state-of-the-art method especially in domains of book and hotel, and is slightly inferior in the domian of electronics.

关键词： Feature extraction Sentiment analysis Mathematical model Time-frequency analysis Analytical models Classification algorithms

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Co-localization in Noisy Images through Minimizing a Ratio Function

Co-localization in Noisy Images through Minimizing a Ratio F...

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International Conference on virtual reality and Visualization (ICVRV)

作者： Chen Wang Jie Xu Yu Zhang Jia Li Xiaowu Chen State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China National Computer Network Emergency Response Technical Team Coordination Center of China

ISBN: (纸本)9781467376747

Object co-localization is a recently proposed vision problem to jointly localize the target object in a collection of images. The main practical challenge for co-localization is the existence of noisy images, in which the target object may be absent. Previous study relied on a prior estimate of the number of noisy images given by human. However, this prior knowledge would be somewhat too strong in practice. To improve on this, we propose a novel formulation for object co-localization in a noisy image collection, which does not rely on any prior knowledge of the noisy images. This is done by incorporating the object co-localization and noisy image identification jointly into a ratio-form objective. We develop an efficient algorithm based on Newton's method for ratio optimization, which can converge to the global optimum in only a few iterations. Extensive experiments conducted on two public benchmarks show that our approach can achieve better or comparable performance compared with several state-of-the-arts, and is robust to different proportions of the noisy images.

关键词： Noise measurement Proposals Robustness Newton method Optimization Training Laplace equations

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Enhancing human pose estimation with temporal clues

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8833卷 357-365页

作者： Hao, Jianliang Zhang, Zhaoxiang Wang, Yunhong State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China

We address the challenging problem of human pose estimation, which can be adopted as a preprocessing step providing accurate and refined humanpose information for gait recognition and other applications. In this paper, we propose a method and augmented Pose-NMS to process the human pose estimation in the consecutive frames based on a reasonable assumption. The poses between the adjacent frames have small changes. Firstly we merge the multiple estimated pose candidates in a single frame to get the representative pose candidates. Then we propagate the final candidate backward and forward to increase the number of the confident candidates based on the Bayesian theory. We apply our method to the Buffy Video dataset and obtain the competitive result to the state-of-art. © Springer International Publishing Switzerland 2014.

关键词： Pattern recognition

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Synthesizing and editing dynamic flames with color temperature

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Chinese Science Bulletin 2014年第36期59卷 5379-5392页

作者： Zhaohui Wu Zhong Zhou Fei Dou Ye Duan Wei Wu State Key Laboratory of Virtual Reality Technology and Systems Beihang University Computer Graphics and Image Understanding Laboratory University of Missouri Columbia MO 65211 USA

Generating computer animated flames is a difficult and computationally expensive problem. Dynamic textures provide an effective means for extrapolating and synthesizing dynamic flames, but aggravates color distortion due to the high correlation of RGB components. A novel method for dynamic flame texture synthesis using color temperature is proposed in this paper. Firstly, the colortemperature mapping is calculated by using the Planck's law and two-color pyrometric technique to avoid color distortion. Secondly, a novel dynamic texture model is presented to transform the RGB space into temperature space. Finally,the dynamic flames editing is presented to support physical temperature adjustment. Experimental results illustrate that our approach is effective to synthesize visually plausible dynamic flames without color distortions and to edit dynamic flames with intuitive physical interpretation.

关键词：纹理合成火焰色温编辑 RGB空间计算问题彩色失真温度调节

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Multi-task rank learning for image quality assessment 40

Multi-task rank learning for image quality assessment

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40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015

作者： Xu, Long Li, Jia Lin, Weisi Zhang, Yongbing Ma, Lin Fang, Yuming Zhang, Yun Yan, Yihua Key Laboratory of Solar Activity National Astronomical Observatories Chinese Academy of Sciences Beijing China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering BeihangUniversity Beijing China International Research Institute for Multidisciplinary Science Beihang University Beijing China Department of Computer Engineering Nanyang Technological University Singapore Graduate School at Shenzhen Tsinghua University Shenzhen China Huawei Noah's Ark Lab Hong Kong School of Information Technology Jiangxi University of Finance and Economics Nanchang China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781467369978

In practice, multiple types of distortions are associated with an image quality degradation process. The existing machine learning (ML) based image quality assessment (IQA) approaches generally established a unified model for all distortion types, or each model is trained independently for each distortion type by using single-task learning, which lead to the poor generalization ability of the models as applied to practical image processing. There are often the underlying cross relatedness amongst these single-task learnings in IQA, which is ignored by the previous approaches. To solve this problem, we propose a multi-task learning framework to train IQA models simultaneously across individual tasks each of which concerns one distortion type. These relatedness can be therefore exploited to improve the generalization ability of IQA models from single-task learning. In addition, pairwise image quality rank instead of image quality rating is optimized in learning task. By mapping image quality rank to image quality rating, a novel no-reference (NR) IQA approach can be derived. The experimental results confirm that the proposed Multi-task Rank Learning based IQA (MRLIQ) approach is prominent among all state-of-the-art NR-IQA approaches. © 2015 IEEE.

关键词： image quality assessment machine learning MOS pairwise comparison Rank learning

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Hybrid Tree Guided Patch Matching

Hybrid Tree Guided Patch Matching

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International Conference on virtual reality and Visualization (ICVRV)

作者： Shibiao Xu Jiguang Zhang Weilong Ding Xukun Shen G. Hemanth Kumar Xiaopeng Zhang National Laboratory of Pattern Recognition Chinese Academy of Sciences Beijing China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Department of Computer Science University of Mysore Mysore India Zhejiang University of Technology Hangzhou China

ISBN: (纸本)9781467376747

Either any of the current global or non-local stereo matching algorithms cannot be good enough to show both matching accuracy and calculation efficiency during the matching processing, especially while there are less texture regions or the images are captured from real scene. Therefore, the goal of our research is to break current bottleneck of stereo matching in aspects of the precision and speed, then get a relatively perfect method compared with other current stereo matching algorithms. Based on this ambitious goal, we proposed hybrid tree guided patch matching algorithm to get a dense and accurate depth image in fast processing speed. We utilize (1) pixel-level and region-level minimum spanning tree to achieve an initial disparity value searching constraint by using hybrid tree cost aggregation, and then (2) apply a robust guided patch matching method to calculate the final accurate disparity of each pixel efficiently by using a cost aggregation restricted through the hybrid tree generated disparity value. In the experience, we demonstrate that our proposed algorithm can generate a high quality depth images and better efficiency compared with recent new stereo matching algorithms. In the Middlebury evaluation, our algorithm also got top ten ranking and better performance among the most of the global stereo matching algorithms in both accuracy and efficiency.

关键词： Estimation Complexity theory Pattern matching Robustness computer vision virtual reality Hybrid power systems

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An orthogonal design-based group search optimizer

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Journal of Computational Information Systems 2014年第10期10卷 4279-4286页

作者： Wang, Dan Xiong, Congcong Huang, Wei School of Computer Science and Information Engineering Tianjin University of Science and Technology Tianjin 300222 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing 100191 China

Group Search Optimizer (GSO) algorithm inspired by the animal behavior has been proven a successful evolutionary algorithm. However, GSO algorithm tends to suffer from premature convergence when dealing with complex problems. This paper presents an enhancing group search optimizer (EGSO), which is realized with the aid of orthogonal design to overcome this limitation. The orthogonal design that is an effective learning method for resolving the local optimization is employed for the evolutionary operations as well as population initialization. Experiments are carried out on a comprehensive set of 19 complex benchmark functions. Experimental Results show that the proposed EGSO leads to better accuracy of solution when compared with the original GSO. 1553-9105/Copyright © 2014 Binary Information Press.

关键词： Evolutionary algorithms

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A spaceborne WAS-GMTI mode based on azimuth multi-channels

A spaceborne WAS-GMTI mode based on azimuth multi-channels

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IET International Radar Conference 2015

作者： Shichao Zheng Jianwei Niu Hui Wang Xiaolei Han State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Institute of Electronics Chinese Academy of Sciences Beijing China Beijing Institute of spacecraft system engineering Beijing China

In this paper, the spaceborne wide-area surveillance ground moving target indication (WAS-GMTI) mode is proposed. In the proposed mode, the requirement of detecting targets from different aspect angles with a high revisit rate can be achieved by modifying the TOPS mode which steers antenna in the azimuth direction. And a three-channel system is chosen to achieve fine GMTI performance. With the three-channel system, the detection of moving targets is realized by displaced phase center antenna (DPCA) technique and the motion parameter is estimated using the interferometric phase. The feasibility of the proposed mode as well as the performance of GMTI is validated by theoretical analysis and simulation experiments.

关键词： ground moving target indication (GMTI) synthetic aperture radar (SAR) terrain observation by progressive scans (TOPS) wide-area surveillance (WAS) Synthetic aperture radar MULTICHANNEL azimuth ground moving target indication ANTENNA antennae ASPECT ANGLE Theoretical analysis

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CodeRepair: PHY-layer partial packet recovery without the pain

CodeRepair: PHY-layer partial packet recovery without the pa...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Jun Huang Guoliang Xing Jianwei Niu Shan Lin Department of Comptuer Science and Engineering Michigan State University MI USA State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Department of Electrical and Computer Engineering Stony Brook University NY USA

Prior studies show that repairing partially corrupted packets, instead of retransmitting them in their entirety, holds potential in improving the performance of 802.11 networks. However, the efficiency of existing packet recovery approaches is severely limited by various overhead associated to redundant transmission and repeated channel contention. In this paper, we propose CodeRepair, a practical coding-based protocol that recovers partially corrupted 802.11 packets without these pains. The design of CodeRepair is based on two novel ideas. First, CodeRepair pushes the limit of 802.11 PHY to piggyback parities in the padded bits of OFDM, obviating the need of transmitting extra information for error correction. Second, CodeRepair corrects errors at the PHY layer, which is significantly more efficient than traditional link-layer approaches. This is due to the fact that a single coded bit usually affects the decoding of a group of data bits in 802.11 convolutional code. As a result, CodeRepair can salvage a partially corrupted packet by correcting a small number of erroneous coded bits using the padded parities. To reduce computational cost of error recovery, CodeRepair employs single parity code for correcting coded bit errors. We propose several techniques to augment the error correcting capability of single parity code without compromising its computation efficiency. Our evaluation shows that CodeRepair recovers an average of 34% partially corrupted packets, and improves the end-to-end link goodput by 59% on lossy 802.11 links.

关键词： IEEE 802.11 Standard Decoding Receivers Reflective binary codes Convolutional codes Forward error correction OFDM

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A high-throughput MQ coder architecture based on dependence extraction method

A high-throughput MQ coder architecture based on dependence ...

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作者： Cao, Haiheng Zhang, Yongfei Jiang, Hongxu Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing100191 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China

ISBN: (纸本)9781479957514

MQ is an efficient entropy coder that performs the actual compression in JPEG2000. However, it usually acts as the bottleneck of the hardware architecture due to the feedback loops caused by iterative operations. The current single ejection (SE) architecture achieves higher frequency by adopting more pipeline stages, but the speed is limited by the throughput per cycle. On the other hand, the multiple ejections (ME) usually handles more than one context data (CxD) per cycle, while the frequency is deteriorated due to the longer critical circuit caused by the context dependences. Hence, to enable the MQ arithmetic coder to process more than one sample while running at higher clock frequency, this paper proposes a two-CxDs architecture based on the equality of two adjacent CxDs, in which the two adjacent CxDs with different contexts are processed in a clock. Experiment results illustrate the architecture increases above 30% speed performance. © 2014 IEEE.

关键词： Extraction

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